Big Data Analytics and Organizational Profitability in Telecommunication Firms in Delta State

Abstract

This study examined the effect of big data analytics on organizational profitability in telecommunication firms in Delta State, Nigeria. Specifically, the study investigated the influence of descriptive analytics and predictive analytics on organizational profitability. A cross-sectional survey research design was adopted to collect quantitative data from employees across selected telecommunication firms. The study population comprised 960 employees, from which a sample size of 282 respondents was determined using Taro Yamane’s formula. A stratified random sampling technique was employed to ensure proportional representation of managerial, technical, and administrative staff. Primary data were collected using structured questionnaires measured on a 5-point Likert scale, while secondary data were used to support and validate findings. Data analysis involved descriptive statistics, Pearson correlation, and multiple regression analysis. Reliability of the instrument was confirmed using Cronbach’s alpha coefficients, all exceeding the acceptable threshold of 0.70. Out of 289 questionnaires distributed, 282 were retrieved, yielding a response rate of 97.6%, with 275 valid responses used for analysis. Descriptive statistics indicated a high level of adoption of both descriptive analytics (mean = 3.87) and predictive analytics (mean = 3.92), alongside a strong perception of organizational profitability (mean = 4.01). Correlation analysis revealed strong positive relationships between descriptive analytics and organizational profitability (r = 0.704, p < 0.01), and between predictive analytics and organizational profitability (r = 0.768, p < 0.01). The regression model demonstrated substantial explanatory power (R² = 0.659), indicating that 65.9% of the variation in organizational profitability is explained by the independent variables. The overall model was statistically significant (F = 238.41, p < 0.001). Regression results showed that both descriptive analytics (β = 0.312, p < 0.001) and predictive analytics (β = 0.489, p < 0.001) have significant positive effects on organizational profitability, with predictive analytics exerting a stronger influence. Consequently, both null hypotheses were rejected. The findings suggest that the adoption and effective utilization of big data analytics significantly enhance organizational profitability, particularly through improved forecasting, decision-making, and strategic planning. The study concludes that telecommunication firms that invest in advanced analytics capabilities are more likely to achieve superior financial performance and sustain competitive advantage.